Computer simulations reveal novel properties of the cell-cell signaling network at the shoot apex in /Arabidopsis

The active transport of the plant hormone auxin plays a major role in the initiation of organs at the shoot apex. Polar localized membrane proteins of the PIN1 family facilitate this transport, and recent observations suggest that auxin maxima created by these proteins are at the basis of organ initiation. This hypothesis is based on the visual, qualitative characterization of the complex distribution patterns of the PIN1 protein in Arabidopsis. To take these analyses further, we investigated the properties of the patterns using computational modeling. The simulations reveal previously undescribed properties of PIN1 distribution. In particular, they suggest an important role for the meristem summit in the distribution of auxin. We confirm these predictions by further experimentation and propose a detailed model for the dynamics of auxin fluxes at the shoot apex

Mechanical constraints imposed by 3D cellular geometry and arrangement modulate growth patterns in the Arabidopsis embryo

Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place

Alignment between PIN1 Polarity and Microtubule Orientation in the Shoot Apical Meristem Reveals a Tight Coupling between Morphogenesis and Auxin Transport

Morphogenesis during multicellular development is regulated by intercellular signaling molecules as well as by the mechanical properties of individual cells. In particular, normal patterns of organogenesis in plants require coordination between growth direction and growth magnitude. How this is achieved remains unclear. Here we show that in Arabidopsis thaliana, auxin patterning and cellular growth are linked through a correlated pattern of auxin efflux carrier localization and cortical microtubule orientation. Our experiments reveal that both PIN1 localization and microtubule array orientation are likely to respond to a shared upstream regulator that appears to be biomechanical in nature. Lastly, through mathematical modeling we show that such a biophysical coupling could mediate the feedback loop between auxin and its transport that underlies plant phyllotaxis

Qualitative modelling and analysis of regulations in multi-cellular systems using Petri nets and topological collections

In this paper, we aim at modelling and analyzing the regulation processes in multi-cellular biological systems, in particular tissues. The modelling framework is based on interconnected logical regulatory networks a la Rene Thomas equipped with information about their spatial relationships. The semantics of such models is expressed through colored Petri nets to implement regulation rules, combined with topological collections to implement the spatial information. Some constraints are put on the the representation of spatial information in order to preserve the possibility of an enumerative and exhaustive state space exploration. This paper presents the modelling framework, its semantics, as well as a prototype implementation that allowed preliminary experimentation on some applications.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Cancer Treatment-Related Fatigue: Psychometric Testing of the Cancer Treatment-Related Fatigue Representation Scale (CTRFRep) in Patients Undergoing Radiation Treatment for Cancer

Indiana University-Purdue University Indianapolis (IUPUI)Cancer treatment-related fatigue (CTRF) is recognized as a prevalent and bothersome symptom for patients with cancer. In a model of the CTRF experience, CTRF representation, or the beliefs, thoughts and emotions surrounding the experience of CTRF, is believed to mediate the relationship between CTRF intensity and CTRF distress. To date, there is no reported measure of CTRF representation. The purpose of this descriptive, cross-sectional study guided by Leventhal’s Common Sense Model of Self-Regulation was to evaluate an instrument designed to measure CTRF representation, the CTRF Representation scale (CTRFRep), based on an existing measure, the Illness Perception Questionnaire (IPQ-R). The study included 47 patients (mean age=57.7 years) receiving radiation therapy for cancer interviewed one month post-treatment. 77% of patients had fatigue during treatment. Three content experts and one theory expert assessed content validity of the CTRFRep. The content experts included three behavioral oncology nurse researchers whose focus is on symptom management and/or fatigue. The theory expert was a nurse researcher who is an expert in the area of self-regulation theory. As tested, the CTRFRep consisted of 105 items in 10 subscales addressing beliefs about the Identity, Timeline (Acute vs. Chronic/Cyclical), Consequences (positive/negative), Cause, Control (Treatment/Personal), Symptom Coherence, and Emotional Representation of CTRF. When evaluating psychometrics, the Identity and Cause subscales are analyzed independent of the other subscales. For the Identity subscale, symptoms most reported as related to CTRF were lack of energy, loss of strength, and feeling blue. For the Cause subscale, the most common beliefs regarding causes of CTRF were cancer treatment(s), having cancer, and stress or worry. Results indicate adequate reliability in six of eight remaining subscales (α>=0.70); the item N in those subscales was reduced from 56 to 34. To address construct validity, logistic regression assessed whether CTRFRep mediated the relationship between CTRF intensity and CTRF distress. After controlling for negative affect, the Identity and Consequences subscales were significant mediators – the Acute vs. Chronic Timeline and Emotional Representation scales were partial mediators – of the relationship between CTRF intensity on CTRF distress. These findings indicate fatigue is a problem for people undergoing treatment for cancer, and the CTRFRep may be a reliable and valid measure of CTRF representation for patients undergoing radiation treatment for cancer. Small sample size prevented successful factor analysis of the CTRFRep. Further research of the CTRFRep is warranted

Making microscopy count: quantitative light microscopy of dynamic processes in living plants

First published: April 2016This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Cell theory has officially reached 350 years of age as the first use of the word ‘cell’ in a biological context can be traced to a description of plant material by Robert Hooke in his historic publication “Micrographia: or some physiological definitions of minute bodies”. The 2015 Royal Microscopical Society Botanical Microscopy meeting was a celebration of the streams of investigation initiated by Hooke to understand at the sub-cellular scale how plant cell function and form arises. Much of the work presented, and Honorary Fellowships awarded, reflected the advanced application of bioimaging informatics to extract quantitative data from micrographs that reveal dynamic molecular processes driving cell growth and physiology. The field has progressed from collecting many pixels in multiple modes to associating these measurements with objects or features that are meaningful biologically. The additional complexity involves object identification that draws on a different type of expertise from computer science and statistics that is often impenetrable to biologists. There are many useful tools and approaches being developed, but we now need more inter-disciplinary exchange to use them effectively. In this review we show how this quiet revolution has provided tools available to any personal computer user. We also discuss the oft-neglected issue of quantifying algorithm robustness and the exciting possibilities offered through the integration of physiological information generated by biosensors with object detection and tracking

The Power of Algorithms and Big Data: A Marketing Perspective on Consumer Manipulation in Business

In marketing, predictive analytics molds big data into tools that can create demographics, target pleasurable neuromodulator chemicals like dopamine, and influence individual and societal behavior patterns. Professionals and scholars alike can use machine-based computation to transform big data into usable knowledge that accurately represents and tracks human behavior. The deception used by marketers to achieve monetary profit can be seen as a direct exploitation of consumers’ trust and privacy. In the past couple of decades this has led to the acceleration of the attention economy and has fueled the age of information. It has pushed countries to not only enforce new laws and regulations, but also race to secure control over data science technologies. Thus, this unchecked greed has created a world in which the power of algorithms and big data is of paramount importance. The future of humanity rides on the success of artificial intelligence algorithms (AI technologies), it is imperative that conversations around this topic become more frequent. The research for this thesis will ultimately lead to a better understanding of how the unregulated dynamic between artificial intelligence programs, big data, corporations, and marketers have had an invasive impact on consumers

A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems

Auxin transport-feedback models of patterning in plants

Many patterning events in plants are regulated by the phytohormone auxin. In fact, so many things are under the influence of auxin that it seems difficult to understand how a single hormone can do so much. Auxin moves throughout the plant via a network of specialized membrane-bound import and export proteins, which are often differentially expressed and polarized depending on tissue type. Here, we review simulation models of pattern formation that are based on the control of these transporters by auxin itself. In these transport-feedback models, diversity in patterning comes not from the addition of more morphogens, but rather by varying the mechanism that regulates the transporters

Multiscale modelling of auxin transport in the plant-root elongation zone

In the root elongation zone of a plant, the hormone auxin moves in a polar manner due to active transport facilitated by spatially distributed influx and efflux carriers present on the cell membranes. To understand how the cell-scale active transport and passive diffusion combine to produce the effective tissue-scale flux, we apply asymptotic methods to a cell-based model of auxin transport to derive systematically a continuum description from the spatially discrete one. Using biologically relevant parameter values, we show how the carriers drive the dominant tissue-scale auxin flux and we predict how the overall auxin dynamics are affected by perturbations to these carriers, for example, in knockout mutants. The analysis shows how the dominant behaviour depends on the cells' lengths, and enables us to assess the relative importance of the diffusive auxin flux through the cell wall. Other distinguished limits are also identified and their potential roles discussed. As well as providing insight into auxin transport, the study illustrates the use of multiscale (cell to tissue) methods in deriving simplified models that retain the essential biology and provide understanding of the underlying dynamics